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A critical factor deciding how much bagging will improve accuracy is the variance of these bootstrap models. We see that BBB with 4 buckets has the largest difference between and . Besides this, BBB with 4 buckets also has the highest standard deviations in predict results. So we choose BBB with 4 buckets as the final method.

We can see that all cases attain best performance when is around 0.06, showing that the choice of is robust. This small optimal value shows that historical records plays an important role for prediction.